1 files changed, 10 insertions, 10 deletions

diff --git a/src/de/lmu/ifi/dbs/elki/database/query/knn/LinearScanPrimitiveDistanceKNNQuery.java b/src/de/lmu/ifi/dbs/elki/database/query/knn/LinearScanPrimitiveDistanceKNNQuery.java
index c4f09744..3f3fbc3f 100644
--- a/src/de/lmu/ifi/dbs/elki/database/query/knn/LinearScanPrimitiveDistanceKNNQuery.java
+++ b/src/de/lmu/ifi/dbs/elki/database/query/knn/LinearScanPrimitiveDistanceKNNQuery.java
@@ -4,7 +4,7 @@ package de.lmu.ifi.dbs.elki.database.query.knn;
  This file is part of ELKI:
  Environment for Developing KDD-Applications Supported by Index-Structures
 
- Copyright (C) 2012
+ Copyright (C) 2013
  Ludwig-Maximilians-Universität München
  Lehr- und Forschungseinheit für Datenbanksysteme
  ELKI Development Team
@@ -29,10 +29,10 @@ import java.util.List;
 import de.lmu.ifi.dbs.elki.database.ids.ArrayDBIDs;
 import de.lmu.ifi.dbs.elki.database.ids.DBIDIter;
 import de.lmu.ifi.dbs.elki.database.ids.DBIDRef;
+import de.lmu.ifi.dbs.elki.database.ids.DBIDUtil;
+import de.lmu.ifi.dbs.elki.database.ids.distance.KNNHeap;
+import de.lmu.ifi.dbs.elki.database.ids.distance.KNNList;
 import de.lmu.ifi.dbs.elki.database.query.distance.PrimitiveDistanceQuery;
-import de.lmu.ifi.dbs.elki.distance.distanceresultlist.KNNHeap;
-import de.lmu.ifi.dbs.elki.distance.distanceresultlist.KNNResult;
-import de.lmu.ifi.dbs.elki.distance.distanceresultlist.KNNUtil;
 import de.lmu.ifi.dbs.elki.distance.distancevalue.Distance;
 
 /**
@@ -74,22 +74,22 @@ public class LinearScanPrimitiveDistanceKNNQuery<O, D extends Distance<D>> exten
   }
 
   @Override
-  public KNNResult<D> getKNNForDBID(DBIDRef id, int k) {
+  public KNNList<D> getKNNForDBID(DBIDRef id, int k) {
     return getKNNForObject(relation.get(id), k);
   }
 
   @Override
-  public List<KNNResult<D>> getKNNForBulkDBIDs(ArrayDBIDs ids, int k) {
+  public List<KNNList<D>> getKNNForBulkDBIDs(ArrayDBIDs ids, int k) {
     final int size = ids.size();
-    final List<KNNHeap<D>> heaps = new ArrayList<KNNHeap<D>>(size);
-    List<O> objs = new ArrayList<O>(size);
+    final List<KNNHeap<D>> heaps = new ArrayList<>(size);
+    List<O> objs = new ArrayList<>(size);
     for(DBIDIter iter = ids.iter(); iter.valid(); iter.advance()) {
-      heaps.add(KNNUtil.newHeap(distanceQuery.getDistanceFactory(), k));
+      heaps.add(DBIDUtil.newHeap(distanceQuery.getDistanceFactory(), k));
       objs.add(relation.get(iter));
     }
     linearScanBatchKNN(objs, heaps);
 
-    List<KNNResult<D>> result = new ArrayList<KNNResult<D>>(heaps.size());
+    List<KNNList<D>> result = new ArrayList<>(heaps.size());
     for(KNNHeap<D> heap : heaps) {
       result.add(heap.toKNNList());
     }